Press & Media

OctOpus in the media

OctOpus automates recurring data-science work for enterprise teams — and the story has been covered on international television, at United Nations forums, and across industry media.

BBC News France 24 ITU WSIS · AI for Good IT for Business Industrial AI Podcast

Coverage

BBC News
OctOpus on BBC News — interview with Maty Sy
Founder Doudou BA discusses OctOpus and automated data science for enterprise teams on BBC News.
Watch the clip
France 24
OctOpus on France 24 — interview with Stéphane Ballong
Television interview on France 24 covering OctOpus and the automation of enterprise data-science work.
Watch the interview
ITU WSIS Forum · AI for Good
Live demonstration with the WMO in Geneva
OctOpus was demonstrated live to World Meteorological Organization executives at the WSIS Forum / AI for Good, showcasing ML on the WMO global data-sharing framework (WIS 2.0).
Read the WMO article
IT for Business
OctOpus featured on IT for Business
Enterprise-IT media coverage of OctOpus and automated data science for business teams.
Watch the segment
Industrial AI Podcast
OctOpus on the Industrial AI Podcast
A conversation about autonomous ML research loops, model validation, and putting data science to work in industrial settings.
Listen to the episode
TikTok
The viral OctOpus demo
A single OctOpus post reached 400K+ impressions and brought in new users and investor conversations. Follow @doudou_octopus for build-in-public updates.
Watch on TikTok

Founder

Doudou BA
Founder & CEO, OctOpus

Doudou built mission-critical data and automation systems used across operations in more than 130 countries before founding OctOpus, and has published peer-reviewed research on machine learning for forecasting and hydrology. OctOpus was demonstrated at the ITU WSIS Forum / AI for Good in Geneva and at VivaTech in Paris.

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Press kit & contact

Writing about OctOpus? The canonical description is: "OctOpus — automated data science for enterprise teams." Give it data and a business objective, and it builds, validates, and delivers the model and report without requiring a data scientist to operate it.